Food allergy in canines: A review
Bibliographic record
Abstract
Food allergy is an immunological response to the ingested allergen present in food like artificial food additives, beef, canned foods, corn, cow milk, dairy products, dog foods, dog biscuits, eggs, fish, and food preservatives, meat of different species including pork, mutton and horse meat, oat meal, potatoes, rice and commonly occurs in dogs and cats. Among all canine species, Labrador and German shepherd were found to be more prone to food allergy and symptoms are similar to other pruritic skin diseases. These food allergies are broadly classified into two categories (1) IgE-mediated food allergy (2) non-IgE-mediated food allergy. Diagnosis can be done by accurate clinical history, parental observations, and laboratory tests: Skin scrapping, bacterial/fungal culture examination, thyroid test, fecal examination and skin biopsy, allergic tests: Patch test, Skin Prick Test, Intra-dermal test and Radioallergosorbent test. Management of these allergies can be done by antihistaminics like Hydroxyzine and Chlorpheniramine, antibiotics like Cephalexin, Enrofloxacin, antifungals like Ketoconazole, Griseofulvin, Amphotericin-B and glucocorticoids like Prednisolone, Methyl prednisolone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".